Based on insights flowing from the Upper Level Math/Stats and Self-Instructional Language (SILP) course sharing pilots, a multi-campus, multidisciplinary Steering Committee and Course Design Task Force are working in concert to explore models and possibilities for course sharing across LACOL’s digital network.
Sharing courses as a consortium can enhance curricular opportunities for students and faculty, lead to efficiency gains by combining expertise and curricular resources, and provide opportunities for our faculty and students to explore digitally-enhanced, collaborative modes for teaching and learning in the liberal arts.
As LACOL is considering a framework for course sharing, a learner-centered course design is recommended to emphasize interpersonal connections and engagement between faculty and students across a shared class. To the extent possible, a level playing field (via technology and pedagogy) should be maintained across local and remote learners. While there is not a one-size-fits all approach, there are plenty of proven models and techniques to draw on. Support for shared courses will depend on a thriving network of relationships across faculty, IT, library, accessibility offices, and other academic support units.
While the consortium expects to be in exploratory mode for the foreseeable future, success of any course sharing initiative critically depends on local champions at the leadership and grass roots levels.
2017 Course Sharing Pilots
Course Sharing for Portuguese (SILP)
In the Fall 2017/Spring 2018, Vassar College and Williams College shared a tutor and teaching resources for their students learning Portuguese via their Self-Instructional Language Programs.
Read more: http://lacol.net/project-summary-silp
Upper Level Math/Stats
In Spring and Fall of 2017, several LACOL colleges collaborated to pilot three shared course offerings for advanced mathematics and statistics:
- Putnam Problem Solving, Spring ‘17 (Prof. S. Miller, WIlliams College)
- Advanced Real Analysis, Fall ‘17 (Prof. S. Garcia, Pomona College)
- Bayesian Statistics, Fall ‘17 (Prof. M. Hu, Vassar College)